Do Artificial Intelligence Systems Understand?

TL;DR

This paper examines whether artificial intelligence systems truly understand or merely process signs, arguing that current mechanistic approaches suffice to explain intelligent behavior without requiring genuine understanding or semantics.

Contribution

It clarifies the relationship between syntax and semantics in AI, emphasizing that understanding is not necessary for intelligent behavior in machines.

Findings

Understanding requires combining rules and intuitions.

Semantics cannot be reduced to syntax.

Mechanistic, syntactic approaches explain current AI capabilities.

Abstract

Are intelligent machines really intelligent? Is the underlying philosophical concept of intelligence satisfactory for describing how the present systems work? Is understanding a necessary and sufficient condition for intelligence? If a machine could understand, should we attribute subjectivity to it? This paper addresses the problem of deciding whether the so-called "intelligent machines" are capable of understanding, instead of merely processing signs. It deals with the relationship between syntaxis and semantics. The main thesis concerns the inevitability of semantics for any discussion about the possibility of building conscious machines, condensed into the following two tenets: "If a machine is capable of understanding (in the strong sense), then it must be capable of combining rules and intuitions"; "If semantics cannot be reduced to syntaxis, then a machine cannot understand." Our conclusion states that it is not necessary to attribute understanding to a machine in order to explain its exhibited "intelligent" behavior; a merely syntactic and mechanistic approach to intelligence as a task-solving tool suffices to justify the range of operations that it can display in the current state of technological development.